Workflow, Alarm Notification and Technology Acceptance of Continuous, Wearable-Based Vital Sign Monitoring on A Neurosurgical Ward–A Pilot Feasibility Study
Year: 2026
Type: article
Abstract: BACKGROUND: Continuous, wearable-based vital sign monitoring can enhance patient safety and reduce intensive care demands but is not routinely used on standard neurosurgical wards. This study assessed alarm events and technology acceptance during the implementation of such a system for postoperative patients in a university hospital's neurosurgical ward. METHODS: In this pilot feasibility study, selected patients were continuously monitored for 12 to 24 hours after elective neurosurgery on a 44-bed ward. Phase 1 (June to December 2019) used 12 mobile units with manual alarm documentation; Phase 2 (August 2023 to January 2024) used 44 fixed bedside units with automatic documentation. Alarm patterns and nurse-rated technology acceptance (4-point Likert scale) were analyzed. RESULTS: Vital signs were monitored in 214 patients (median age: 58, IQR: 42 to 70) in Phase 1 and 290 patients (median age: 60, IQR: 43 to 77) in Phase 2. Procedures included cranial, spinal, and peripheral nerve surgeries. Phase 1 recorded 30 nonclinical alarms and no clinical alarms. In contrast, Phase 2 registered 14,500 clinical and 185,744 nonclinical alarms, mostly from detached sensors (177,989/185,744; 96%). Clinical alarms were mainly due to hypoxia (8305/14,500; 57%) and tachycardia (3487/14,500; 30%). Most alarms were acknowledged within 30 seconds (clinical: 12,969/14,500; 90% and nonclinical: 181,447/185,744; 98%), with delayed responses mostly for nonclinical events (3625/4189; 87%). Nurses reported improved convenience, usability, and system connection in Phase 2. CONCLUSIONS: Wearable-based vital sign monitoring is feasible on neurosurgical wards, but high nonclinical alarm rates highlight the need to refine alarm management strategies for effective clinical integration.
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W7123544207